Blue Noise Plots
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
We propose Blue Noise Plots, two-dimensional dot plots that depict data points of univariate data sets. While often onedimensional strip plots are used to depict such data, one of their main problems is visual clutter which results from overlap. To reduce this overlap, jitter plots were introduced, whereby an additional, non-encoding plot dimension is introduced, along which the data point representing dots are randomly perturbed. Unfortunately, this randomness can suggest non-existent clusters, and often leads to visually unappealing plots, in which overlap might still occur. To overcome these shortcomings, we introduce Blue Noise Plots where random jitter along the non-encoding plot dimension is replaced by optimizing all dots to keep a minimum distance in 2D i. e., Blue Noise. We evaluate the effectiveness as well as the aesthetics of Blue Noise Plots through both, a quantitative and a qualitative user study. The Python implementation of Blue Noise Plots is available here.
Description
@article{10.1111:cgf.142644,
journal = {Computer Graphics Forum},
title = {{Blue Noise Plots}},
author = {Onzenoodt, Christian van and Singh, Gurprit and Ropinski, Timo and Ritschel, Tobias},
year = {2021},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.142644}
}